Literature DB >> 24235291

Combining motor imagery with selective sensation toward a hybrid-modality BCI.

Lin Yao, Jianjun Meng, Dingguo Zhang, Xinjun Sheng, Xiangyang Zhu.   

Abstract

A hybrid modality brain-computer interface (BCI) is proposed in this paper, which combines motor imagery with selective sensation to enhance the discrimination between left and right mental tasks, e.g., the classification between left/ right stimulation sensation and right/ left motor imagery. In this paradigm, wearable vibrotactile rings are used to stimulate both the skin on both wrists. Subjects are required to perform the mental tasks according to the randomly presented cues (i.e., left hand motor imagery, right hand motor imagery, left stimulation sensation or right stimulation sensation). Two-way ANOVA statistical analysis showed a significant group effect (F (2,20) = 7.17, p = 0.0045), and the Benferroni-corrected multiple comparison test (with α = 0.05) showed that the hybrid modality group is 11.13% higher on average than the motor imagery group, and 10.45% higher than the selective sensation group. The hybrid modality experiment exhibits potentially wider spread usage within ten subjects crossed 70% accuracy, followed by four subjects in motor imagery and five subjects in selective sensation. Six subjects showed statistically significant improvement ( Benferroni-corrected) in hybrid modality in comparison with both motor imagery and selective sensation. Furthermore, among subjects having difficulties in both motor imagery and selective sensation, the hybrid modality improves their performance to 90% accuracy. The proposed hybrid modality BCI has demonstrated clear benefits for those poorly performing BCI users. Not only does the requirement of motor and sensory anticipation in this hybrid modality provide basic function of BCI for communication and control, it also has the potential for enhancing the rehabilitation during motor recovery.

Mesh:

Year:  2013        PMID: 24235291     DOI: 10.1109/TBME.2013.2287245

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  15 in total

1.  Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms.

Authors:  Bin He; Bryan Baxter; Bradley J Edelman; Christopher C Cline; Wendy Ye
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2015-05-20       Impact factor: 10.961

Review 2.  Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface.

Authors:  Lichao Xu; Minpeng Xu; Tzyy-Ping Jung; Dong Ming
Journal:  Cogn Neurodyn       Date:  2021-04-10       Impact factor: 3.473

Review 3.  A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives.

Authors:  Inchul Choi; Ilsun Rhiu; Yushin Lee; Myung Hwan Yun; Chang S Nam
Journal:  PLoS One       Date:  2017-04-28       Impact factor: 3.240

4.  Recent Advances in Hybrid Brain-Computer Interface Systems: A Technological and Quantitative Review.

Authors:  Sahar Sadeghi; Ali Maleki
Journal:  Basic Clin Neurosci       Date:  2018-09-01

5.  Toward a hybrid brain-computer interface based on repetitive visual stimuli with missing events.

Authors:  Yingying Wu; Man Li; Jing Wang
Journal:  J Neuroeng Rehabil       Date:  2016-07-26       Impact factor: 4.262

Review 6.  Steady-State Somatosensory Evoked Potential for Brain-Computer Interface-Present and Future.

Authors:  Sangtae Ahn; Kiwoong Kim; Sung Chan Jun
Journal:  Front Hum Neurosci       Date:  2016-01-14       Impact factor: 3.169

7.  Enhanced Motor Imagery-Based BCI Performance via Tactile Stimulation on Unilateral Hand.

Authors:  Xiaokang Shu; Lin Yao; Xinjun Sheng; Dingguo Zhang; Xiangyang Zhu
Journal:  Front Hum Neurosci       Date:  2017-12-01       Impact factor: 3.169

8.  Exploring Training Effect in 42 Human Subjects Using a Non-invasive Sensorimotor Rhythm Based Online BCI.

Authors:  Jianjun Meng; Bin He
Journal:  Front Hum Neurosci       Date:  2019-04-17       Impact factor: 3.169

9.  Mirror Visual Feedback Combining Vibrotactile Stimulation Promotes Embodiment Perception: An Electroencephalogram (EEG) Pilot Study.

Authors:  Li Ding; Jiayuan He; Lin Yao; Jinyang Zhuang; Shugeng Chen; Hewei Wang; Ning Jiang; Jie Jia
Journal:  Front Bioeng Biotechnol       Date:  2020-10-26

10.  Systems Neuroengineering: Understanding and Interacting with the Brain.

Authors:  Bradley J Edelman; Nessa Johnson; Abbas Sohrabpour; Shanbao Tong; Nitish Thakor; Bin He
Journal:  Engineering (Beijing)       Date:  2016-03-16       Impact factor: 7.553

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.